In commercial web search today, users typically submit short queries, which are then matched against a large set of documents. Often, a simple keyword search against the documents does not suffice to provide desired results, as many words in the query have semantic meaning that dictates evaluation. Consider for example a query such as “popular digital camera around $425”. Performing a plain keyword match over a set of documents will not produce matches for cameras priced at $420 or $430, and so forth, even though such matches are very likely what the user is seeking.
At the same time, more desirable search results for many users may be found within a more focused set of data rather than the large set of documents that is traditionally searched. For example, the above query may provide more desirable results for many users if data related to shopping is searched, rather than a large collection of many unrelated web pages.